Viewpoint-Based Similarity Discernment on SNAP
Summary :
This paper presents an algorithm for viewpoint-based similarity discernment of linguistic concepts on Semantic Network Array Processor (SNAP). The viewpoint-based similarity discernment plays a key role in retrieving similar propositions. This is useful for advanced knowledge processing areas such as analogical reasoning and case-based reasoning. The algorithm assumes that a knowledge base is constructed for SNAP, based on information acquired from the WordNet linguistic database. The algorithm identifies paths on the knowledge base between each given concept and a given viewpoint concept, then computes a similarity degree between the two concepts based on the number of nodes shared by the paths. A small scale knowledge base was constructed and an experiment was conducted on a SNAP simulator that demonstrated the feasibility of this algorithm. Because of SNAP's scalability, the algorithm is expected to work similarly on a large scale knowledge base.
- Publication
- IEICE TRANSACTIONS on Information Vol.E82-D No.2 pp.500-502
- Publication Date
- 1999/02/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Artificial Intelligence and Cognitive Science
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Takashi YUKAWA, Sanda M. HARABAGIU, Dan I. MOLDOVAN, "Viewpoint-Based Similarity Discernment on SNAP" in IEICE TRANSACTIONS on Information,
vol. E82-D, no. 2, pp. 500-502, February 1999, doi: .
Abstract: This paper presents an algorithm for viewpoint-based similarity discernment of linguistic concepts on Semantic Network Array Processor (SNAP). The viewpoint-based similarity discernment plays a key role in retrieving similar propositions. This is useful for advanced knowledge processing areas such as analogical reasoning and case-based reasoning. The algorithm assumes that a knowledge base is constructed for SNAP, based on information acquired from the WordNet linguistic database. The algorithm identifies paths on the knowledge base between each given concept and a given viewpoint concept, then computes a similarity degree between the two concepts based on the number of nodes shared by the paths. A small scale knowledge base was constructed and an experiment was conducted on a SNAP simulator that demonstrated the feasibility of this algorithm. Because of SNAP's scalability, the algorithm is expected to work similarly on a large scale knowledge base.
URL: https://global.ieice.org/en_transactions/information/10.1587/e82-d_2_500/_p
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@ARTICLE{e82-d_2_500,
author={Takashi YUKAWA, Sanda M. HARABAGIU, Dan I. MOLDOVAN, },
journal={IEICE TRANSACTIONS on Information},
title={Viewpoint-Based Similarity Discernment on SNAP},
year={1999},
volume={E82-D},
number={2},
pages={500-502},
abstract={This paper presents an algorithm for viewpoint-based similarity discernment of linguistic concepts on Semantic Network Array Processor (SNAP). The viewpoint-based similarity discernment plays a key role in retrieving similar propositions. This is useful for advanced knowledge processing areas such as analogical reasoning and case-based reasoning. The algorithm assumes that a knowledge base is constructed for SNAP, based on information acquired from the WordNet linguistic database. The algorithm identifies paths on the knowledge base between each given concept and a given viewpoint concept, then computes a similarity degree between the two concepts based on the number of nodes shared by the paths. A small scale knowledge base was constructed and an experiment was conducted on a SNAP simulator that demonstrated the feasibility of this algorithm. Because of SNAP's scalability, the algorithm is expected to work similarly on a large scale knowledge base.},
keywords={},
doi={},
ISSN={},
month={February},}
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TY - JOUR
TI - Viewpoint-Based Similarity Discernment on SNAP
T2 - IEICE TRANSACTIONS on Information
SP - 500
EP - 502
AU - Takashi YUKAWA
AU - Sanda M. HARABAGIU
AU - Dan I. MOLDOVAN
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E82-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 1999
AB - This paper presents an algorithm for viewpoint-based similarity discernment of linguistic concepts on Semantic Network Array Processor (SNAP). The viewpoint-based similarity discernment plays a key role in retrieving similar propositions. This is useful for advanced knowledge processing areas such as analogical reasoning and case-based reasoning. The algorithm assumes that a knowledge base is constructed for SNAP, based on information acquired from the WordNet linguistic database. The algorithm identifies paths on the knowledge base between each given concept and a given viewpoint concept, then computes a similarity degree between the two concepts based on the number of nodes shared by the paths. A small scale knowledge base was constructed and an experiment was conducted on a SNAP simulator that demonstrated the feasibility of this algorithm. Because of SNAP's scalability, the algorithm is expected to work similarly on a large scale knowledge base.
ER -
English
